October 14, 2022
| Time | Activity |
|---|---|
| 13:00 | Welcome and Orientation |
| 13:15 | TALK: Hugo Ledoux |
| 13:45 | Guidelines for Reproducing and Reviewing |
| 14:10 | Select papers, chat and coffee |
| 14:20 | Round I of ReproHacking |
| 15:20 | Re-group and sharing of experiences |
| 15:30 | Coffee break |
| 15:45 | Round II of ReproHacking - Complete Feedback form |
| 16:45 | Re-group and sharing of experiences |
| 16:55 | Feedback and Closing |
“Computational notebooks […] open up the world of analytics to […] disciplines that encompass diverse methodologies and skillsets [such as] urban planning […] Some urban planners focus on policymaking […] Others employ qualitative methods to work in and with vulnerable communities. Others develop simulation models to forecast urbanization patterns and infrastructure needs. Others intermingle these, and many more, different approaches to understanding and shaping the city. Yet all urban planners benefit [or should!] from basic quantitative literacy and an ability to reason critically with data. This scholarly and professional imperative aligns with the growing importance of computational thinking in the urban context and parallel trends in geocomputation […], geographic data science […], and the open-source/open-science movements […].” (Boeing, 2019, p. 40)
“toolkits relying on point-and-click interfaces are inefficient in the era of big data. Due to the limited scope for automation of tasks, not only is workflow efficiency reduced but also the reproducibility of the underlying research is compromised, because this largely depends on the (often undocumented) sequence of decisions manually operating the software. […] We then argue that the field [of urban morphology] needs a shift from dominant traditional geographic information system (GIS) environments based on a graphical user interface (GUI; e.g., QGIS or ArcMap) towards reproducible open code-based workflows.” (Fleischmann et al., 2022, p. 3)
Organization: tools to organize your projects so that you don’t have a single folder with hundreds of files
Automation: the power of scripting to create automated data analyses
Documentation: difference between binary files (e.g. docx) and text files and why text files are preferred for documentation
Dissemination: publishing is not the end of your analysis, rather it is a way station towards your future research and the future research of others
Checklist available in documents/checklist.md
Important! Reproducibility is hard! Without submitting authors there would be no ReproHack. Constructive criticism only please!